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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Continuous improvement for existing solutions | 25% | |
| Topic 2: Design solutions for organizational complexity | 26% | |
| Topic 3: Design for new solutions | 29% | |
| Topic 4: Accelerate workload migration and modernization | 20% |
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NEW QUESTION # 390
A solutions architect is designing a network for a new cloud deployment. Each account will need autonomy to modify route tables and make changes. Centralized and controlled egress internet connectivity is also needed.
The cloud footprint is expected to grow to thousands of AWS accounts.
Which architecture will meet these requirements?
Answer: A
Explanation:
Explanation
https://docs.aws.amazon.com/whitepapers/latest/building-scalable-secure-multi-vpc-network-infrastructure/centr
https://docs.aws.amazon.com/whitepapers/latest/building-scalable-secure-multi-vpc-network-infrastructure/centr AWS Transit Gateway helps you design and implement networks at scale by acting as a cloud router. As your network grows, the complexity of managing incremental connections can slow you down. AWS Transit Gateway connects VPCs and on-premises networks through a central hub. This simplifies your network and puts an end to complex peering relationships -- each new connection is only made once.
NEW QUESTION # 391
A solutions architect is reviewing an application's resilience before launch. The application runs on an Amazon EC2 instance that is deployed in a private subnet of a VPC.
The EC2 instance is provisioned by an Auto Scaling group that has a minimum capacity of I and a maximum capacity of I.
The application stores data on an Amazon RDS for MySQL DB instance. The VPC has subnets configured in three Availability Zones and is configured with a single NAT gateway.
The solutions architect needs to recommend a solution to ensure that the application will operate across multiple Availability Zones.
Which solution will meet this requirement?
Answer: C
NEW QUESTION # 392
A global company runs an analytics application on Amazon EC2 for computing. The company uses Amazon EBS as primary storage for raw and processed data. Users manually upload raw data daily to Amazon EC2 by using SSH from a local on-premises storage computer. The analytics application processes the data and a user manually uploads the data to Amazon S3 for long-term storage.
The company wants to containerize the processing logic and migrate the processing logic to Amazon EKS.
The company needs an automated solution to upload and move the processed data. The solution must have multiprotocol support and be usable from the EKS cluster.
Which solution meets these requirements with the LEAST operational effort?
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
This explanation is based on AWS documentation and best practices but is paraphrased, not a literal extract.
The company wants to move from a manual EC2 and EBS-based workflow to a containerized application on Amazon EKS and automate data movement. The solution must:
* Support automated transfer of raw and processed data.
* Offer multiprotocol support.
* Be directly usable from the EKS cluster as a mounted volume.
* Minimize operational effort by using managed services where possible.
AWS DataSync is a managed service designed to move data between on-premises storage and AWS storage services or between AWS storage services. It can perform scheduled or continuous transfers with minimal operational overhead. For storage accessible from Amazon EKS, a shared file system that supports mounting as a volume is appropriate.
Amazon FSx for NetApp ONTAP provides a fully managed file system with multiprotocol support, including NFS and SMB, and supports features such as snapshots and storage efficiencies. Because it supports multiple protocols, it satisfies the requirement for multiprotocol access and can be mounted by applications running in Amazon EKS using standard Kubernetes persistent volume mechanisms.
In the correct solution (option C), DataSync is used to copy raw data from the on-premises environment to FSx for NetApp ONTAP. The FSx for NetApp ONTAP file system is then mounted as a volume in the EKS cluster, allowing the containerized analytics processing logic to read and write data directly. After processing, DataSync is again used to copy processed data from FSx for NetApp ONTAP to Amazon S3 for long-term storage. This leverages DataSync's native integration with both FSx for NetApp ONTAP and Amazon S3, and avoids the need to run or manage custom upload tooling.
Option A uses Amazon EFS, which supports NFS but does not provide multiprotocol support (for example, SMB), so it does not fully meet the multiprotocol requirement. It also introduces AWS Transfer for SFTP for the processed data upload, which adds an additional managed endpoint and SFTP-based flow, increasing complexity relative to using DataSync end-to-end.
Option B uses Amazon FSx for Lustre, which is optimized for high-performance compute workloads and integrates well with S3, but it is not a multiprotocol file system and is typically accessed via NFS. It does not meet the stated multiprotocol requirement.
Option D uses FSx for NetApp ONTAP (which supports multiprotocol) but relies on AWS Transfer for SFTP to move processed data to S3. While this can work, it adds another managed input endpoint and requires SFTP client configuration and management. Using DataSync directly from FSx for NetApp ONTAP to Amazon S3 (as in option C) is more straightforward, better suited for automated large-scale transfers, and involves less operational overhead.
Therefore, option C meets all the requirements with the least operational effort by using DataSync with FSx for NetApp ONTAP and S3.
References:AWS documentation on AWS DataSync for automated, scheduled data transfers between on- premises storage, FSx file systems, and Amazon S3.AWS documentation on Amazon FSx for NetApp ONTAP including its multiprotocol support (NFS and SMB) and integration with Kubernetes and Amazon EKS.
NEW QUESTION # 393
A company is planning a large event where a promotional offer will be introduced. The company's website is hosted on AWS and backed by an Amazon RDS for PostgreSQL DB instance. The website explains the promotion and includes a sign-up page that collects user information and preferences Management expects large and unpredictable volumes of traffic periodically which will create many database writes A solutions architect needs to build a solution that does not change the underlying data model and ensures that submissions are not dropped before they are committed to the database
Which solutions meets these requirements'?
Answer: D
NEW QUESTION # 394
A company runs an loT platform on AWS loT sensors in various locations send data to the company's Node js API servers on Amazon EC2 instances running behind an Application Load Balancer The data is stored in an Amazon RDS MySQL DB instance that uses a 4 TB General Purpose SSD volume The number of sensors the company has deployed in the field has increased over time and is expected to grow significantly The API servers are consistently overloaded and RDS metrics show high write latency Which of the following steps together will resolve the issues permanently and enable growth as new sensors are provisioned, while keeping this platform cost-efficient? {Select TWO.)
Answer: A,D
Explanation:
Option C is correct because leveraging Amazon Kinesis Data Streams and AWS Lambda to ingest and process the raw data resolves the issues permanently and enable growth as new sensors are provisioned. Amazon Kinesis Data Streams is a serverless streaming data service that simplifies the capture, processing, and storage of data streams at any scale. Kinesis Data Streams can handle any amount of streaming data and process data from hundreds of thousands of sources with very low latency. AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. Lambda can be triggered by Kinesis Data Streams events and process the data records in real time. Lambda can also scale automatically based on the incoming data volume. By using Kinesis Data Streams and Lambda, the company can reduce the load on the API servers and improve the performance and scalability of the data ingestion and processing layer3 Option E is correct because re-architecting the database tier to use Amazon DynamoDB instead of an RDS MySQL DB instance resolves the issues permanently and enable growth as new sensors are provisioned. Amazon DynamoDB is a fully managed key-value and document database that delivers single-digit millisecond performance at any scale. DynamoDB supports auto scaling, which automatically adjusts read and write capacity based on actual traffic patterns. DynamoDB also supports on-demand capacity mode, which instantly accommodates up to double the previous peak traffic on a table. By using DynamoDB instead of RDS MySQL DB instance, the company can eliminate high write latency and improve scalability and performance of the database tier.
NEW QUESTION # 395
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